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Hi,
I am trying to use Algorithm Framework to model an intraday strategy that buy on market open and sell and market close, How can I emit insight only when the market is open/close for symbols?
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Hey Supanat,
This kind of strictly scheduled algorithm works best a classic algorithm with scheduled events. Insights in the framework are meant to be predictions that can be acted on. However it is possible to implement what you wish using the framework.
Instead of using scheduled events, you can hard code time restrictions for buying and selling in the Update method of your AlphaModel. You can enter long on a trade with InsightDirection.Up and exit a trade with InsightDirection.Flat.
class MyAlpha(AlphaModel):
def __init__(self):
self.day = 0
def Update(self, algorithm, data):
insights = []
if self.day == algorithm.Time.day:
return insights
marketClose = None
for symbol in data.Keys:
if marketClose is None:
marketClose = algorithm.Securities[symbol].Exchange.Hours.GetNextMarketClose(algorithm.Time, False)
insights.append(Insight.Price(symbol, marketClose, InsightDirection.Up))
return insights
Here's an example.
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The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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